The NERD algorithm performs calculations with increased accuracy, displaying results almost in real-time.
Project description
NERD: Numerical Estimation of Rodenticide Density
The eradication of rodents is central to island restoration efforts and the aerial broadcast of rodenticide bait is the preferred dispersal method. To improve accuracy and expedite the evaluation of aerial operations, we developed an algorithm for the numerical estimation of rodenticide density (NERD). The NERD algorithm performs calculations with increased accuracy, displaying results almost in real-time. NERD describes the relationship between bait density, the mass flow rate of rodenticide through the bait bucket, and helicopter speed and produces maps of bait density on the ground. NERD also facilitates the planning of helicopter flight paths and allows for the instant identification of areas with low or high bait density.
Installation 🏗️
To install from pip:
pip install geci-nerd
or clone directly from Github
git clone git@github.com:IslasGECI/nerd.git
cd nerd
and install from source
pip install --editable .
geci-nerd
is developed under Python >= 3.8. 🐍
Jupyter Notebook Demonstrations 📒
You can explore the functionality of NERD through interactive Jupyter notebooks. These are the options to access the demonstration notebooks:
- View a static version on GitHub. Simply navigate to the calibration-demo and tiling_demo notebooks.
- Alternatively, you can run the Jupyter notebooks locally using Docker. Follow the instructions below:
First, pull the latest demo image:
docker pull islasgeci/nerd_demo:latest
Then, run the container:
docker run --detach --publish 8080:8888 --rm islasgeci/nerd_demo
Lastly, explore the Jupyter notebooks at http://localhost:8080/
References ✏️
- Rojas-Mayoral, E. (2019) «Improving the efficiency of aerial rodent eradications by means of the numerical estimation of rodenticide density». Island invasives: scaling up to meet the challenge, IUCN. doi: 10.5281/zenodo.10214344.
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